[1] 葛斐，荣秀婷，石雪梅，等. 基于经济、气象因素的安徽省年最大负荷预测方法研究 [J]. 中国电力，2015，48(3): 84-87.

GE F, RONG X T, SHI X M，et al. The anhui annual maximum load forecasting method research based on economic and meteorological factors [J]. Electric Power，2015，48(3): 84-87.
[2]

MAKSIMOVICH S M, SHILJKUT V M. The peak load forecasting afterwards its intensive reduction [J]. IEEE Transactions on Power Delivery，2009，24(3): 1552-1559.
[3] 王建军. 智能电网环境下的自适互动智能负荷预测研究 [J]. 陕西电力，2010，38(5): 11-15.

WANG J J. Research on adaptive interactive intelligent load forecasting in smart grid environment [J]. Shanxi Electric Power，2010，38(5): 11-15.
[4] 周潮，邢文洋，李宇龙. 电力系统负荷预测方法综述 [J]. 电源学报，2012，10(6): 32-39.

ZHOU C, XING W Y, LI Y L. Summarization on load forecasting method of electrical power system [J]. Journal of Power Supply，2012，10(6): 32-39.
[5] 杨双吉，董青峰. 产值单耗法在负荷预测中的应用 [J]. 华北水利水电学院学报，2009，30(6)73-76.

YANG S J, DONG Q F. Application of unit consumption method of output value in load forecasting [J]. Journal of North China Institute of Water Conservancy and Hydroelectric Power，2009，30(6): 73-76.
[6] 王俊，席芳. 万山海岛地区太阳能资源变化特征分析及评估 [J]. 南方能源建设，2015，2(1): 193-197.

WANG J, XI F．Variation characteristics and assessment of solar energy resources in Wanshan islands area [J]. Southern Energy Construction，2015，2(1): 193-197.
[7] 陈志巧. 基于模糊理论的电力负荷预测研究 [J]. 山东科技大学学报(自然科学版)，2006，25(2): 81-83.

CHEN Z Q. Study of power load forecast based on the fuzzy theory [J]. Journal of Shangdong University of Science and Technology(Natural Science)，2006，25(2): 81-83.
[8] 赵艳丽. 基于显著性理论的电力建设工程投资灰色预测 [J]. 南方能源建设，2014，1(1): 97-100.

ZHAO Y L. Study on grey forecast method for power construction engineering investment based on the cost-significant theory [J]. Southern Energy Construction，2014，1(1): 97-100.
[9] 饶国燃，梁平. 支持向量机及其在社会总用电量预测中的运用 [J]. 广东电力，2008，21(11): 22-24.

RAO G R, LIANG P. Support vector machine and its application in forecasting of total power consumption of society [J]. Guangdong Electric Power，2008，21(11): 22-24.
[10] 田野. 基于动量因子的神经网络群电流负荷预测模型 [J]. 电力系统保护与控制，2016，44(17): 31-38.

TIAN Y. A forecasting model for current load of neural network group based upon momentum factor [J]. Power System Protection and Control，2016，44(17): 31-38.
[11]

GEETA P, Bhim S, BIJAYA K P. Back-propagation algorithm-based controller for autonomous Wind-DG microgrid [J]. IEEE Transactions on Industry Applications，2016，52(5): 4408-4415.
[12]

FU X G, LI S H, MICHAEL F，et al. Training recurrent neural networks with the levenberg-marquardt algorithm for optimal control of a grid-connected converte r[J]. IEEE Transactions on Neural Networks and Learning Systems，2015，26(9): 1900-1912.
[13] 侯亚丽，李铁. 基于LM优化算法的BP神经网络目标识别方法 [J]. 探测与控制学报，2008，30(1): 53-57.

HOU Y L, LI T. Improvement of BP neural network by LM optimizing algorithm in target identification [J]. Journal of Detection & Control，2008，30(1): 53-57.
[14] 牛东晓，曹树华，卢建昌，等. 电力负荷预测技术及其应用 [M]. 北京：中国电力出版社，2009.

NIU D X, CAO S H, LU J C，et al. Power load forecasting technology and its application [M]. Beijing：China Electric Power Press，2009.
[15] 刘平原，张磊，王宇，等. 基于多元线性回归分析的110 kV及以上电压等级变压器主材用量计算模型研究 [J]. 广东电力，2016，29(7): 59-66.

LIU P Y, ZHANG L, WANG Y，et al. Research on calculation model for amount of primary materials of 110 kV and above transformers based on multiple linear regression analysis [J]. Guangdong Electric Power，2016，29(7): 59-66.
[16] 唐详玲，王平，李思岑，等. 基于方差—协方差组合预测的中长期电力负荷预测研究 [J]. 电气技术，2015，16(1): 15-18.

TANG X L, WANG P, LI S C，et al. Research on medium and long-term electric load forecasting based on variance-covariance combined Model [J]. Electrical Engineering，2015，16(1): 15-18.